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Add XGBoostRegressor for freqAI, fix mypy errors

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This commit is contained in:
Emre
2022-09-08 14:12:19 +03:00
parent 4c9ac6b7c0
commit d7ca203cf0
6 changed files with 87 additions and 9 deletions
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8
freqtrade/freqai/prediction_models/BaseRegressionModel.py
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@@ -20,7 +20,7 @@ class BaseRegressionModel(IFreqaiModel):
"""
def train(
self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen
self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen, **kwargs
) -> Any:
"""
Filter the training data and train a model to it. Train makes heavy use of the datakitchen
@@ -67,7 +67,7 @@ class BaseRegressionModel(IFreqaiModel):
return model
def predict(
self, unfiltered_dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = False
self, dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = False, **kwargs
) -> Tuple[DataFrame, npt.NDArray[np.int_]]:
"""
Filter the prediction features data and predict with it.
@@ -78,9 +78,9 @@ class BaseRegressionModel(IFreqaiModel):
data (NaNs) or felt uncertain about data (PCA and DI index)
"""
dk.find_features(unfiltered_dataframe)
dk.find_features(dataframe)
filtered_dataframe, _ = dk.filter_features(
unfiltered_dataframe, dk.training_features_list, training_filter=False
dataframe, dk.training_features_list, training_filter=False
)
filtered_dataframe = dk.normalize_data_from_metadata(filtered_dataframe)
dk.data_dictionary["prediction_features"] = filtered_dataframe